Background: Risky drinking is prevalent among women of childbearing age. Although many women reduce their drinking during pregnancy, more than half return to prepregnancy levels during the early postpartum period. Risky drinking in new mothers may be associated with negative child and maternal health outcomes; however, new mothers are unlikely to seek treatment for risky drinking because of stigma and fear of child protective service involvement. SMS text messaging is a promising approach for reaching non–treatment-seeking new mothers at risk because of risky drinking. SMS text messaging interventions (TMIs) are empirically supported for alcohol use, but a tailored intervention for new mothers does not exist. This study aims to fill this gap by developing a just-in-time adaptive TMI for postpartum risky drinking.
Objective: The objectives of this paper are to present a preliminary conceptual model of postpartum risky drinking and describe the protocol for conducting an ecological momentary assessment (EMA) study with new mothers to inform the refinement of the conceptual model and development of the TMI.
Methods: This paper presents a preliminary conceptual model of postpartum risky drinking based on the motivational model of alcohol use, social cognitive theory, and temporal self-regulation theory. The model proposes three primary intervention targets: motivation, self-efficacy, and self-regulation. Theoretical and empirical literature in support of the conceptual model is described. The paper also describes procedures for a study that will collect EMA data from 30 participants recruited via social media and the perinatal Central Intake system of New Jersey. Following the baseline assessment, EMA surveys will be sent 5 times per day for 14 days. The assessment instruments and data analysis procedures are described.
Results: Recruitment is scheduled to begin in January 2022 and is anticipated to conclude in March 2022. Study results are estimated to be published in July 2022.
Conclusions: The study findings will enhance our understanding of daily and momentary fluctuations in risk and protective factors for risky drinking during the early postpartum period. The findings will be used to refine the conceptual model and inform the development of the TMI. The next steps for this work include the development of intervention components via an iterative participatory design process and testing of the resulting intervention in a pilot microrandomized trial.
International Registered Report Identifier (IRRID): PRR1-10.2196/36849
Background and Rationale
Risky drinking, defined as the consumption of ≥4 drinks in a day or ≥8 drinks in a week [- ], is prevalent among women of childbearing age. A 2019 national survey found that, among women aged 18-25 years, 55% reported past-month alcohol use, 34% reported past-month binge drinking (defined as drinking ≥4 drinks at once), and 7% reported past-month heavy alcohol use (defined as drinking ≥4 drinks at once at least 5 days in the previous month). Among women aged 26-44 years, 59% reported past-month alcohol use, 30% reported past-month binge drinking, and 6% reported past-month heavy alcohol use [ ]. Although many women reduce their drinking during pregnancy, more than half return to prepregnancy levels by 3 months after delivery [ , ]. Patterns of postpartum drinking vary widely, with 8%-12% of women showing patterns of escalating risky drinking in the early postpartum period [ - ]. Depending on severity, postpartum alcohol use can lead to impaired parenting and an increased risk of child maltreatment [ ], which can have devastating impacts on brain development, leading to long-term impairment [ , ]. Given the increase in drinking and the potential for severe consequences to the child [ - ], the postpartum period is a critical time for intervention to address risky drinking. However, most adults who engage in risky drinking do not seek treatment [ ]. New mothers may be particularly unlikely to seek treatment because of stigma and fear of child protective service involvement [ ]. Thus, there is a critical need for innovative approaches to reach non–treatment-seeking new mothers at high risk for negative consequences associated with risky drinking. The goal of this study is to meet this need by developing an SMS text messaging intervention (TMI) to address postpartum risky drinking. In this paper, we describe two critical first steps toward this goal: (1) development of a preliminary conceptual model of postpartum risky drinking and (2) presentation of a protocol for data collection via ecological momentary assessment (EMA) to refine the conceptual model and inform TMI development.
SMS text messaging is a promising approach for reaching non–treatment-seeking risky drinkers and may be particularly suitable for addressing postpartum risky drinking. With 97% of Americans owning a cell phone as of 2021, access to SMS text messaging is widespread . Studies suggest that 99% of received SMS text messages are opened, and 90% are read within 3 minutes of receipt [ ]. TMIs are highly acceptable to people with drug and alcohol dependence [ ] and have high scalability potential at a relatively low cost. Of particular importance for new mothers, TMIs provide a way of delivering interventions anonymously, potentially overcoming the stigma and fear of consequences that often prevent mothers from accessing more traditional forms of treatment [ , - ]. In a recent survey, low-income new mothers with histories of risky drinking reported high levels of mobile phone ownership and use of SMS text messaging as well as favorable reactions to receiving SMS text messages to address alcohol use [ ].
A growing body of literature demonstrates support for TMIs in reducing risky drinking in non–treatment-seeking adults [, - ]. In a recent review of mobile health interventions for unhealthy alcohol use, over half of the TMIs reviewed were effective in reducing alcohol use or increasing readiness to change [ ]. However, the existing literature on TMIs for alcohol use has several limitations, including a lack of theoretical behavior change models guiding intervention design, small samples, and lack of long-term follow-up [ , , ]. In addition, most existing studies have compared whole TMIs to attention- or assessment-only controls and were not able to disentangle the impacts of individual intervention components. Generalizability is also limited as most studies have focused on college drinkers, adults with alcohol use disorder, or patients in the emergency department. There are currently no TMIs for alcohol use that are tailored to the unique characteristics of the postpartum period.
TMIs that tailor content to specific participant characteristics or clinical needs show larger effects on clinical outcomes and lower rates of attrition than programs that deliver generic messages [, , ]. Interventions that are dynamically tailored in response to reports of changing needs or other variables assessed regularly throughout intervention delivery are referred to as just-in-time adaptive interventions (JITAIs). JITAIs aim to provide interventions at times when individuals are particularly vulnerable and when opportunity for positive change is greatest [ ], making this approach a good fit for the postpartum period. The postpartum period is inherently a time of high vulnerability, as demonstrated by higher rates of depression and perceived stress among new mothers [ ], which are known risk factors for alcohol use [ - ]. New mothers experience unique transient influences on vulnerability, including daily stress associated with caring for a new baby that can be exacerbated by factors such as lack of sleep and baby irritability [ - ]. The postpartum period is also a time of opportunity for positive change. Pregnant and postpartum people generally report high levels of motivation to change behaviors that may negatively affect their baby, making this time of life a teachable moment with maximum potential for effecting positive behavior change [ ].
This study will apply the multiphase optimization strategy (MOST) framework  to develop and pilot-test the first theory-driven just-in-time adaptive TMI for postpartum risky drinking. The MOST is an engineering-inspired framework that allows for the identification of the optimal package of intervention components and is recommended for building efficient, scalable mobile health interventions [ ]. The MOST proceeds in 3 phases. The preparation phase, which is the focus of this study, is aimed at (1) developing a conceptual model that specifies the relationships between intervention components, intervention targets, and outcomes; (2) developing content and delivery strategies for each intervention component; and (3) pilot-testing the developed intervention components. In the optimization phase, the intervention components are further tested in an efficient experimental design with the goal of identifying the best combination of components [ ]. Finally, the evaluation phase consists of a traditional randomized controlled trial comparing the full intervention package with a suitable control group.
Following the MOST framework, the first step in developing a theory-driven JITAI for postpartum risky drinking is to specify the theoretical pathways from the postpartum risk factors that are the primary intervention targets to the ultimate desired outcome of reduced risky drinking. Our proposed conceptual model (described in the Methods section) is based on three theoretical frameworks that have been widely used to explain alcohol and substance use: the motivational model of alcohol use , social cognitive theory [ ], and temporal self-regulation theory [ ]. These theories have been used previously in the development of TMIs for alcohol use [ - ] but have never been applied to risky drinking in the postpartum period. On the basis of these theories, we have identified three core intervention targets: motivation, defined as commitment to avoid drinking [ ]; self-efficacy, including self-efficacy to avoid drinking and self-efficacy in the maternal role; and self-regulation, defined by the use of a range of adaptive coping strategies. All 3 intervention targets correspond to behavior change techniques that have demonstrated efficacy in the context of brief interventions for alcohol use [ - ]. All 3 theoretical frameworks describe internal and external contextual variables operating as risk and protective factors for the intervention targets that ultimately affect drinking behavior. On the basis of the theoretical frameworks as well as the limited empirical literature on the postpartum period, we have selected the following internal and external factors for inclusion: mood, stress, and fatigue (internal factors), and baby fussiness, social support, and drinking cues (external factors). Empirical literature supporting the conceptual model and the selection of contextual variables is described in the Methods section.
As JITAIs aim to intervene at the momentary level, a comprehensive understanding of the daily and momentary fluctuations in risks and protective factors for postpartum risky drinking is needed to inform the design of a tailored JITAI for this population. EMAs collect data in real time over the course of a day and are designed to capture momentary fluctuations in feelings and behaviors as participants go about their daily lives . EMAs are particularly suitable for tracking changes in state-level characteristics, which are thought to change significantly within short periods. This method has been widely used in research on substance use and other health behaviors [ - ]. In total, 2 EMA studies with new mothers [ , ] offer preliminary support for the feasibility of this approach with this population. However, almost nothing is known about the in-the-moment predictors of daily drinking in the postpartum period, information that is crucial for the design of effective interventions for this population.
The objectives of this paper are to (1) present a preliminary conceptual model of postpartum risky drinking and (2) describe the protocol for conducting an EMA study with new mothers to inform the refinement of the conceptual model and the development of a just-in-time adaptive TMI to address postpartum risky drinking.
The purpose of the EMA study is to assess and refine the conceptual model and test the feasibility of EMA data collection procedures in a sample of new mothers. The primary research questions of the EMA study are as follows: (1) How do momentary and daily fluctuations in internal and external contextual factors affect motivation, self-efficacy, and self-regulation? (2) Which internal and external factors are most salient at particular times of the day? (3) What is the relationship between maternal self-efficacy and drinking self-efficacy and how does this relationship fluctuate throughout the day? (4) What is the relationship between momentary and daily changes in motivation, self-efficacy, and self-regulation and daily drinking? (5) To what extent are the study methods (eg, number and length of surveys and item wording) acceptable and feasible for the target population of new mothers within the early postpartum period?
This EMA study is part of a 3-year effort to develop a JITAI for postpartum risky drinking that comprises the preparation phase of the MOST framework (). EMA data collection represents the first stage of this work, aimed at refining a conceptual model of postpartum risky drinking and informing JITAI development. This paper presents our preliminary conceptual model of postpartum risky drinking and our protocol for EMA data collection. Following completion of the EMA, components of the JITAI will be developed via an iterative participatory design process with focus groups of new mothers. Finally, the resulting JITAI will be tested in a pilot microrandomized trial.
The study was approved by the Solutions Institutional Review Board in October 2020 (#2020/06/15) and registered at ClinicalTrials.gov. All study participants will provide informed consent to take part.
Our preliminary conceptual model was developed via a review of relevant theoretical and empirical literature combined with a series of brainstorming conversations among the study team.depicts the proposed conceptual model of postpartum risky drinking that guided the development of our EMA data collection protocol. This model is preliminary and subject to adjustment based on the findings of the EMA study. Drawing from the motivational model of alcohol use [ ], social cognitive theory [ ], and temporal self-regulation theory [ ], this model identifies three core intervention targets (motivation, self-efficacy, and self-regulation) that have been reliably assessed at the momentary or daily level in EMA studies. This section describes the empirical literature that supports our conceptual model organized according to the intervention target.
According to the motivational model of alcohol use, motivation to drink is the most proximal predictor of drinking behavior . Our conceptual model operationalizes motivation as commitment to avoid drinking, consistent with other studies examining within-day fluctuations in motivation as a key mechanism of change in substance use treatment [ , , ]. Measured in this way, motivation has been found to fluctuate within a single day, and these changes were associated with drinking the following day [ ].
The motivational model proposes four types of drinking motives that may affect within-day fluctuations in motivation to drink: coping (aimed at reducing negative emotions), enhancement (aimed at increasing positive emotions), conformity (aimed at avoiding social rejection), and social (aimed at increasing positive social experiences), with varying antecedents and consequences of each . Findings from EMA studies of alcohol motivations demonstrate that motives vary within persons and across time and situations in response to internal and external contextual factors [ ]. Previous EMA studies suggest that higher positive affect is associated with greater enhancement motives [ - ] and higher negative affect is associated with greater coping motives at the daily level [ , ]. Studies examining links between drinking motives and outcomes have shown that daily enhancement motives are generally associated with poorer daily drinking outcomes [ , , ]. Findings for coping motives are less consistent, with some studies finding that coping motives are associated with increased quantity and severity of alcohol use [ , ] and others finding no relationship [ , , ]. Most existing research has been conducted with college student samples, and there may be different patterns among new mothers, which we will begin to elucidate in this study.
Consistent with social cognitive theory, the conceptual model suggests that two types of self-efficacy—drinking self-efficacy and maternal self-efficacy—may contribute to drinking behavior. Drinking self-efficacy, defined as a person’s belief in their ability to avoid drinking, is well-supported as a significant predictor of drinking behavior. Higher drinking self-efficacy has been shown to predict less drinking and improved long-term outcomes in the context of treatment for alcohol use disorder [- ]. Studies with individuals who engage in problematic drinking and are treatment-seeking have found that daily within-person change in self-efficacy to avoid drinking is associated with intensity of drinking the next day [ , ].
In addition to drinking self-efficacy, our conceptual model includes self-efficacy specific to the maternal role, defined as a mother’s belief in her ability to successfully care for her baby. There is currently no research examining associations between maternal self-efficacy and alcohol use. In addition, no study to date has examined daily or momentary changes in maternal self-efficacy during the postpartum period despite evidence that self-efficacy in other domains changes over brief periods [, , ]. This study will explore the associations between maternal self-efficacy and drinking at the daily and momentary levels to inform whether maternal self-efficacy may be an important intervention target for new mothers who engage in risky drinking.
Both drinking self-efficacy and maternal self-efficacy are influenced by internal and external contextual factors, as reflected in the conceptual model. Variations in mood, stress, and fatigue have been shown to affect both drinking self-efficacy [, , ] and maternal self-efficacy [ - ]. In addition, maternal self-efficacy is affected by difficult infant behavior [ , , , ] and a lack of social support [ - ]. The model also includes a feedback loop between self-efficacy, daily drinking, and mastery such that mastery experiences can increase self-efficacy, thereby reducing the likelihood of next-day drinking. For example, a successful attempt to avoid drinking is likely to increase an individual’s belief in their own capacity to avoid drinking in the future, and this heightened self-efficacy makes them more likely to succeed in future attempts to avoid drinking. Empirical studies on the mastery feedback loop are limited, but there is some support for the reciprocal relationship between mastery and self-efficacy in a sample of adults who smoke [ ].
According to temporal self-regulation theory, self-regulation, or the ability to monitor and adapt cognitions, emotions, and behaviors in response to internal or external contextual factors in a goal-directed manner, is a key factor affecting risky behaviors, including alcohol use [, ]. Internal and external factors can act as triggers for substance use, and adaptive self-regulation strategies must be applied to avoid drinking alcohol in the presence of these triggers [ ]. In addition, internal and external factors can predict the likelihood that a person will apply self-regulation strategies in a particular situation [ , ]. Self-regulation is a core theoretical mechanism of behavior change in cognitive behavioral treatments for addiction [ , ], although findings related to the effectiveness of specific self-regulatory strategies for alcohol use have been mixed [ ].
A small number of studies have examined daily within-person changes in self-regulation strategies in the context of alcohol use . Studies typically define self-regulation as the use of adaptive coping strategies [ , , ] or protective drinking strategies [ , ]. Daily engagement in coping strategies has been associated with drinking behavior, with some studies finding differences based on the specific strategy used [ , ] and others not [ ]. Given that nearly all studies have used college student samples and there is no research to guide the selection of specific strategies for new mothers, our study includes a broad range of self-regulation strategies with the aim of determining those most salient for our target population.
Target Population, Eligibility Criteria, and Sample Size
The study target population is adults aged 18-45 years who live in New Jersey and gave birth to a live infant within the previous 2 weeks who is currently in their care. This study is being conducted in New Jersey to leverage existing partnerships between the study team and the New Jersey state system of care for perinatal women. Additional eligibility criteria include speaking English and access to a smartphone with internet. Participants must also report one of the following: (1) a score of ≥2 on the Tolerance, Annoyance, Cut Down, Eye-Opener (T-ACE) alcohol risk screener, (2) having ≥8 standard drinks in 1 week in the 12 months before becoming pregnant, or (3) having ≥4 drinks at one time once a month or more often in the 12 months before becoming pregnant. We aim to recruit 30 participants who meet the eligibility criteria. Similar sample sizes have been used in other EMA studies of individuals who engage in substance use [- ] and new mothers [ ].
Recruitment, Eligibility Screening, and Informed Consent Procedures
This study will use two primary recruitment strategies: (1) recruitment via social media advertisements on Facebook and Instagram and (2) referrals from providers in the New Jersey perinatal Central Intake (CI) system.
Social Media Recruitment
Advertisements for the study will be placed on Facebook and Instagram and will be geographically targeted to New Jersey. Additional advertisement targeting will include interests related to birth, pregnancy, motherhood, infant care, and drinking alcohol. Individuals who click on an advertisement will be directed to the study website. Social media recruitment via Facebook and Instagram is widely used in research study recruitment and has been used successfully with both new mothers [- ] and individuals who are using substances [ , ]. Individuals who access the study website via a social media advertisement will have the option to complete eligibility screening and informed consent on the web or to connect directly with the study coordinator and complete the process via phone.
New Jersey operates a state-wide CI system that provides a single point of entry into services for pregnant and postpartum people to promote improved care coordination and access to needed services. For this study, we will partner with one of the CI sites that serves a large, demographically diverse county in the state. CI workers will introduce the study to their clients using a script provided by the study team. If a client is interested in learning more about the study, the CI worker will provide their contact information to the study coordinator, who will contact the client within 2 weeks of her due date to complete eligibility screening. For clients who are interested in the study but prefer not to share their contact information, the CI worker will direct them to the study website, where they can complete eligibility screening and informed consent on the web.
Baseline Survey and EMA Training
Eligible participants who complete the informed consent process will be invited to complete the baseline survey. Baseline survey data will be used to describe the study sample and understand the impact of baseline characteristics on momentary changes in the variables of interest. The baseline survey can be completed either on the web via Qualtrics (Qualtrics International Inc) or via phone with the study coordinator, depending on the participant’s preference. The baseline survey will take approximately 30 minutes to complete, and participants will receive a US $25 gift card upon completion. The baseline survey will assess demographic characteristics, maternal self-efficacy, mental health, stress and coping, motivation, alcohol use, and other substance use. Seefor a complete list of the baseline measures. Following completion of the baseline survey, participants will complete a one-on-one 30-minute EMA training session with the study coordinator via Zoom. During the training, the study coordinator will instruct the participants in the installation and use of the MetricWire (MetricWire Inc) data collection app as well as in best practices for maintaining privacy throughout the study. Participants will be considered enrolled in the study after they complete both the baseline survey and EMA training.
|Demographics||Age, gender, marital status, race, ethnicity, living arrangements, childbirth history, education, employment, income, and substance use treatment history||—a|
|Drinking self-efficacy||Perceived ability to handle various drinking situations||Drinking Refusal Self-efficacy Questionnaire–Revised |
|Alcohol and drug use history||Use of alcohol, marijuana, and illegal drugs before pregnancy, during pregnancy, and since giving birth||Adapted from the NIDAb-modified ASSISTc ; NIAAAd drinking questions [ ]|
|Motivation||Readiness to change alcohol use||Maternal Motivation Scale |
|Postpartum depression||Symptoms of depression since giving birth||Beck Depression Scale |
|Maternal self-efficacy||Confidence in carrying out various baby care tasks||Karitane Parenting Confidence Scale |
|Trauma history||Experiences of trauma during childhood||Adverse Childhood Experiences Questionnaire |
|Pandemic stress||Stress related to the COVID-19 pandemic||Adapted from the Pandemic Stress Index |
|Attachment to infant||Mother experience of bonding and attachment to baby||Infant Bonding Scale |
|Fatigue||Experiences of emotional and physical fatigue||Fatigue Assessment Scale |
|Stress||Perceptions of stress related to general life experiences||Perceived Stress Scale–4 |
|Drinking motives||Motivation to consume alcohol||Drinking Motives Questionnaire–Revised |
|Coping self-efficacy||Perceived ability to cope with challenging life events||Coping Self-efficacy Scale |
|Social support||Perceptions of social support||Interpersonal Support Evaluation List–12 |
|Digital literacy||Comfort using technology to complete tasks, such as SMS text messaging, using a smartphone, and accessing health information on the web||Media and Technology Usage and Attitudes Scale ; the eHealth Literacy Scale [ ]|
aThere is no specific citation for the demographic items.
bNIDA: National Institute on Drug Abuse.
cASSIST: Alcohol, Smoking, and Substance Involvement Screening Test.
dNIAAA: National Institute on Alcohol Abuse and Alcoholism.
EMA Data Collection Procedures
All EMA data will be collected via the MetricWire app. The MetricWire app is available for free download from the Apple App Store and Google Play Store and has been used in other EMA research studies [, ]. The participants will use their own smartphones to complete the EMA surveys 5 times daily for 14 days. The five surveys will include a morning survey, which is a daily diary asking about the previous day, and 4 shorter hourly surveys, which ask questions about the period since the previous survey. The selection of 5 daily surveys is based on the need to balance desire to assess fluctuations in risk factors with considerations of participant burden [ ], and 3-4 surveys a day has been found to be acceptable to young mothers [ ].
displays a sample daily schedule of EMA prompts. Upon enrollment in the study, the participants will be asked to select a morning start time for receiving messages each day. Each day, the morning survey will be sent within 1 hour after the selected start time and will ask questions about the previous day. The morning survey should take approximately 2-3 minutes to complete and will remain available for 10 hours before expiring.
The remainder of the day will be divided into 4 equal segments, and hourly surveys will be sent randomly within each segment. No surveys will be sent later than 9 PM. After each survey prompt, the survey will be available for up to 60 minutes, with 2 reminder prompts sent at 20 and 40 minutes. Surveys that are not completed within the 60-minute window will expire. Completion of each hourly survey will take 1-2 minutes.
Between the last survey in the evening and the first survey in the morning, an optional EMA survey will be available for the participants to complete. The reason for this optional survey is to enable data collection during the night, when the participants may be awake with their baby. Nights may be times of high stress and high risk of drinking for new mothers. This survey will allow us to capture data on these middle-of-the-night times without disturbing the participants by sending prompts. The participants who complete the night survey will receive an automatic response SMS text message with contact information for a 24-hour support hotline.
Study participants will be remunerated for taking part in the study in the form of gift cards to Amazon or Target. The participants will be paid US $25 for completion of the baseline survey. During EMA data collection, the participants will be paid US $2 for each EMA survey completed, with a bonus of US $20 for completing >50% of the EMA surveys and US $30 for completing >80% of the EMA surveys. Bonus incentives are used routinely in EMA studies to boost compliance and have been used in EMA studies with postpartum women . The participants will be able to view their progress toward earning bonus incentives within the MetricWire app.
To ensure that the participants are adequately supported during the study, we will engage in the following: (1) check in briefly by phone with all participants after 3 days of EMA to obtain initial feedback on the questions and address any technical difficulties, (2) provide information on how to obtain immediate support via hotlines, and (3) provide all participants with a list of local mental health and substance use treatment and support resources at the outset of the study. Information about how to obtain immediate support will be available within the MetricWire app at all times for the participants to access as needed.
The study team reviewed the existing literature and selected EMA measures that align with each construct in the conceptual model (). As EMA measures must be brief, we prioritized measures that have been used in other EMA studies, particularly those used with a similar population. For measures that have not been used in previous EMA studies, we reviewed factor analyses of full-length scales and selected the highest-loading items to represent the constructs of interest. For some items, we adapted the wording to fit the momentary nature of the EMA. The final list of items included in the morning and hourly EMA surveys is shown in organized according to the constructs in the conceptual model. At the beginning of each survey, the participant is asked to indicate how much time they spent with their baby the previous day (morning survey), whether they were with their baby since the previous survey, and whether they will be with their baby in the next hour (hourly survey). Responses determine which survey questions are asked based on skip patterns. For example, participants who report that they were not with their baby since the previous survey will not be asked how many times their baby fussed or cried since the last survey. The morning survey includes a total of 23 items, and the hourly surveys include a total of 14 items.
|Construct, subcategories, and measure (reference)||Item (response options)||Morning||Hourly|
|Adapted from the studies by Nguyen et al , Godell et al [ ], and Thrul et al [ ]||✓|
|Adapted from the Perceived Stress Scale ; single item used in previous EMA studies [ , ]||✓|
|Adapted from the Fatigue Assessment Scale ||✓|
|Adapted from the studies by Dennis and Ross  and Mendez et al [ ]||✓|
|Selected items from the Infant Characteristics Questionnaire ||✓|
|Adapted from the study by Adams et al ||✓|
|Item from the Maternal Social Support Index ||✓|
|Adapted from the study by McQuoid et al ||✓|
|Selected items from the Drinking Motives Questionnaire ||✓|
|Commitment to avoid drinking|
|Adapted from the study by Kuerbis et al ||✓||✓|
|Developed for this study||✓||✓|
|Adapted from the study by Kuerbis et al ||✓||✓|
|Adapted from the studies by Roos et al  and Cambron et al [ ]||✓||✓|
|Adapted from the studies by Roos et al  and Cambron et al [ ]|
|Selected items from the Perceived Maternal Parenting Self-efficacy Tool ||✓|
|Developed for this study||✓|
|Adapted from the studies by O’Donnell et al  and Thrul et al [ ]||✓|
Acceptability and Feasibility
Drawing from other EMA feasibility studies [, , - ], feasibility outcomes will include the percentage of EMA surveys completed each day, each week, and at the end of the 14-day period; the percentage of each EMA measure completed; and the percentage of respondents who completed 50% and 80% of the EMA surveys [ , ]. Acceptability measures will be collected via a short text-based survey at the end of the 14-day EMA period and will include an assessment of technical challenges, burden, emotional response, and overall satisfaction using Likert scale items from other EMA studies [ , - ].
Compliance Monitoring Strategies
We will apply the following established methods to encourage and monitor compliance: (1) one-on-one training on EMA procedures before the start of data collection [, , , - ], (2) availability of technical support by phone throughout the EMA period [ , , ], (3) daily SMS text message reminders to complete the EMA surveys [ , ], (4) bonus incentives for completing >50% and >80% of the EMA surveys [ , , ], (5) keeping the participants informed of their progress toward earning bonus incentives [ , ], and (6) outreach to participants who did not complete any EMA surveys 3 days in a row [ , ]. If 3 days pass without any EMA responses, the participants will receive an automated SMS text message reminding them to complete the surveys. The reminder message will be sent once per day for 5 days. If there is still no response, the participant will be considered dropped from the study.
As the primary purpose of the EMA is to inform the development of the JITAI, the analyses will be largely descriptive. To avoid issues of data quality stemming from noncompliance, we will exclude participants who complete <50% of the required EMA surveys . On the basis of rates of EMA compliance in studies of young adults who drink alcohol [ , ] and of postpartum women [ , ], we expect that nearly all participants will complete ≥50% of the EMAs. We will use descriptive statistics to describe the baseline characteristics of the study sample as well as the feasibility outcomes. Patterns of missing data in the EMA surveys will be studied using frequency distributions and graphs to discern whether there are certain times when participants are more or less responsive to prompts. We will also examine the average time to respond following each prompt. As in other EMA studies [ ], the variation in response to each variable will be graphed using scatter plots with a Loess smoother and examined visually to detect patterns in fluctuations within and across days. To test associations among variables, we will apply generalized estimating equations following the procedures used by Nguyen et al [ ] and Thrul et al [ ], testing linear and quadratic effects. Generalized estimating equations account for the nesting of multiple observations within participants [ ]. To inform the selection of decision rules for the JITAI, we will examine associations among predictors (internal and external factors), mediators (intervention targets), and outcomes (daily drinking) based on individual EMA surveys and averaged across each day. To inform the selection of tailoring variables, we will examine variability in internal and external factors across EMA surveys as well as variability in their relations to the primary intervention targets (motivation, self-efficacy, and self-regulation). For these analyses, the internal and external factors will be examined as time-varying predictors of intervention targets as recommended by Shiffman [ ]. We will assess participant differences in EMA feasibility and acceptability measures using independent sample 2-tailed t tests and repeated-measures analyses of variance.
Recruitment for this study is scheduled to begin in January 2022. We anticipate completing recruitment and enrollment by March 2022 and expect to have completed EMA data collection by April 1, 2022. Study results will be published in peer-reviewed scientific journals upon completion of data analysis, which is estimated to be in July 2022.
This paper presents a preliminary conceptual model of postpartum risky drinking as well as a protocol for an EMA data collection study aimed at refining the conceptual model and informing the development of the first JITAI for postpartum risky drinking. This study is the first to assess in-the-moment predictors of risky drinking in the postpartum period and will thus fill critical gaps in existing research. New mothers who engage in risky drinking and other substance use are understudied and underserved as much of the intervention research on perinatal substance use is focused on pregnancy despite high risks of increasing substance use in the early postpartum weeks .
The study findings will enhance our understanding of daily and momentary fluctuations in risk and protective factors for risky drinking during the early postpartum period, a time when risk for alcohol use is high and access to treatment is often low . Although there is substantial theoretical and empirical literature on the risk and protective factors for risky drinking in the general adult population [ , , ], this study will be the first to examine whether established models apply to the unique population of new mothers. In addition, the study findings will elucidate the role of maternal-specific factors such as baby fussiness and maternal self-efficacy in postpartum risky drinking. Very little is currently known about alcohol use risk during the early postpartum weeks, and data gleaned from this study will provide the information needed to develop tailored interventions for this underserved and high-risk population.
Strengths and Limitations
A primary strength of this study is the reliance on theory to guide EMA data collection and JITAI development. A recent systematic review of JITAIs for substance use found that most existing studies did not apply state-of-the-art methods such as the MOST framework and did not sufficiently incorporate theory into intervention development . The base of empirical studies on brief interventions for postpartum risky drinking is extremely small, and those studies that do exist have not adequately incorporated theoretically driven behavior change techniques [ ]. Thus, the JITAI to ultimately be developed in this study stands to significantly improve upon existing interventions by including specific behavior change techniques that are clearly mapped onto theory. Studies show that TMIs that integrate behavior change principles and are adaptively tailored generate larger effects on clinical outcomes [ , ].
The inclusion of variables that are especially salient in the postpartum period, such as maternal self-efficacy, baby irritability, and sleep, is an additional strength of this study. Studies of mothers in substance use treatment demonstrate a complex relationship between motherhood and substance use treatment and recovery. Although motherhood and caring for children are often described as a critical motivating factor for seeking treatment and reducing substance use [, ], mothers are also more likely to conceal their substance use and avoid seeking help because of fears of losing their children [ , ]. Loss of child custody may also lead to relapse in mothers because of the stress and trauma of child removal [ , ]. Given these complex relationships, assessing variables related to the mother’s role, such as maternal self-efficacy, is critical for the appropriate tailoring of interventions.
Study limitations include the requirement to speak and read English and own a smartphone with internet access, limiting generalizability. In addition, the study is focused on alcohol use only, which may leave needs related to the use of other substances unaddressed. Many pregnant and postpartum people who engage in risky drinking also use other substances [, ]. Finally, participant noncompliance and attrition is often a limitation of EMA studies [ ]. Although the few previous EMA studies that have been conducted with new mothers report compliance rates of 75%-80% [ , ], one of the goals of this study is to assess the feasibility of the EMA protocol in this understudied population to inform future research.
Conclusions and Future Directions
The need for tailored digital supportive interventions for the postpartum period is greater than ever given the increasing rates of perinatal stress, depression, and substance use during the COVID-19 pandemic . A growing number of studies have shown increases in postpartum anxiety and depression, perinatal stress, and difficulties with bonding and breastfeeding since the beginning of the pandemic [ , ], all of which significantly increase the risk for risky drinking. This increased risk is combined with the fact that women who use substances are less likely to receive postpartum care [ ] and are more likely to report poor relationships with their health care providers and negative experiences seeking care [ ]. Digital interventions are generally acceptable to new mothers as a way of receiving support for risky drinking and other behavioral health concerns [ , ] and have the potential to fill a significant gap in services that is currently being exacerbated by the pandemic.
Despite the limitations, this study has the potential to significantly contribute to the existing literature by improving our understanding of the antecedents of postpartum risky drinking and informing the development of a tailored JITAI to address it. If feasibility is supported, the EMA protocol can also serve as a model for future studies that aim to collect real-time data from new mothers. This study represents a first step in a larger program of research aimed at using technology to reach underserved new mothers with interventions for perinatal substance use that are evidence-based and tailored to their identities as mothers and aim to empower mothers to seek help while reducing stigma and fear. The methods and findings of this study will be applied to future efforts to ultimately expand the JITAI to include other substances beyond alcohol as well as to create culturally tailored versions. Significant racial and ethnic disparities exist in access to support and treatment for substance use, with Black and Latinx mothers experiencing higher levels of stigma and greater access barriers to obtaining needed support [, ]. An important future direction for our research program is to partner with Black and Latinx communities to develop theory-driven, tailored, and technology-based interventions to better meet the needs of Black and Latinx new mothers.
This study is funded by the National Institute on Alcohol Abuse and Alcoholism (grant R34AA028407; seefor grant reviews). The authors acknowledge their partners at Prevent Child Abuse New Jersey for their contributions to this study.
Conflicts of Interest
National Institute on Alcohol Abuse and Alcoholism grant reviews.PDF File (Adobe PDF File), 148 KB
- Nayak MB, Kaskutas LA, Mericle AA. Randomized trial of an innovative electronic screening and brief intervention for reducing drinking among women of childbearing age. J Addict Med 2019;13(6):450-459 [FREE Full text] [CrossRef] [Medline]
- Grant BF, Chou SP, Saha TD, Pickering RP, Kerridge BT, Ruan WJ, et al. Prevalence of 12-month alcohol use, high-risk drinking, and DSM-IV alcohol use disorder in the united states, 2001-2002 to 2012-2013: results from the National Epidemiologic Survey on alcohol and related conditions. JAMA Psychiatry 2017 Sep 01;74(9):911-923 [FREE Full text] [CrossRef] [Medline]
- Fleming MF, Lund MR, Wilton G, Landry M, Scheets D. The Healthy Moms Study: the efficacy of brief alcohol intervention in postpartum women. Alcohol Clin Exp Res 2008 Sep;32(9):1600-1606 [FREE Full text] [CrossRef] [Medline]
- Center for Behavioral Health Statistics and Quality. Results from the 2019 National Survey on Drug Use and Health: detailed tables. Substance Abuse and Mental Health Services Administration, Rockville, MD. 2020. URL: https://www.samhsa.gov/data/sites/default/files/reports/rpt29394/NSDUHDetailedTabs2019/NSDUHDetTabsAppB2019.htm [accessed 2022-03-24]
- Forray A, Merry B, Lin H, Ruger JP, Yonkers KA. Perinatal substance use: a prospective evaluation of abstinence and relapse. Drug Alcohol Depend 2015 May 01;150:147-155 [FREE Full text] [CrossRef] [Medline]
- Jagodzinski T, Fleming MF. Postpartum and alcohol-related factors associated with the relapse of risky drinking. J Stud Alcohol Drugs 2007 Nov;68(6):879-885 [FREE Full text] [CrossRef] [Medline]
- Liu W, Mumford EA, Petras H. Maternal alcohol consumption during the perinatal and early parenting period: a longitudinal analysis. Matern Child Health J 2016 Feb;20(2):376-385. [CrossRef] [Medline]
- Laborde ND, Mair C. Alcohol use patterns among postpartum women. Matern Child Health J 2012 Dec;16(9):1810-1819 [FREE Full text] [CrossRef] [Medline]
- Wilson J, Tay RY, McCormack C, Allsop S, Najman J, Burns L, et al. Alcohol consumption by breastfeeding mothers: frequency, correlates and infant outcomes. Drug Alcohol Rev 2017 Sep;36(5):667-676. [CrossRef] [Medline]
- Institute of Medicine, National Research Council. New Directions in Child Abuse and Neglect Research. Washington, DC: The National Academies Press; 2014.
- National Scientific Council on the Developing Child. The Science of Neglect: The Persistent Absence of Responsive Care Disrupts the Developing Brain: Working Paper 12. Boston, MA: Center on the Developing Child at Harvard University; 2012.
- Rossow I, Felix L, Keating P, McCambridge J. Parental drinking and adverse outcomes in children: a scoping review of cohort studies. Drug Alcohol Rev 2016 Jul;35(4):397-405 [FREE Full text] [CrossRef] [Medline]
- Jester JM, Jacobson SW, Sokol RJ, Tuttle BS, Jacobson JL. The influence of maternal drinking and drug use on the quality of the home environment of school-aged children. Alcohol Clin Exp Res 2000 Aug;24(8):1187-1197. [Medline]
- Pajulo M, Pyykkönen N, Kalland M, Sinkkonen J, Helenius H, Punamäki R, et al. Substance-abusing mothers in residential treatment with their babies: importance of pre- and postnatal maternal reflective functioning. Infant Ment Health J 2012 Jan;33(1):70-81 [FREE Full text] [CrossRef] [Medline]
- Raitasalo K, Holmila M, Jääskeläinen M, Santalahti P. The effect of the severity of parental alcohol abuse on mental and behavioural disorders in children. Eur Child Adolesc Psychiatry 2019 Jul;28(7):913-922 [FREE Full text] [CrossRef] [Medline]
- Witkiewitz K, Dearing RL, Maisto SA. Alcohol use trajectories among non-treatment-seeking heavy drinkers. J Stud Alcohol Drugs 2014 May;75(3):415-422 [FREE Full text] [Medline]
- Stone R. Pregnant women and substance use: fear, stigma, and barriers to care. Health Justice 2015 Feb 12;3(1):2-16. [CrossRef]
- Mobile fact sheet. Pew Research Center. 2021. URL: https://www.pewresearch.org/internet/fact-sheet/mobile/ [accessed 2022-01-15]
- Johnson D. SMS marketing open rates exceed 99%. Tatango, Inc. 2019. URL: https://www.tatango.com/blog/sms-open-rates-exceed-99/#:~:text=The%20main%20reason%20SMS%20open,sending%20them%20an%20SMS%20message [accessed 2022-01-15]
- Tofighi B, Nicholson JM, McNeely J, Muench F, Lee JD. Mobile phone messaging for illicit drug and alcohol dependence: a systematic review of the literature. Drug Alcohol Rev 2017 Dec;36(4):477-491 [FREE Full text] [CrossRef] [Medline]
- Fowler LA, Holt SL, Joshi D. Mobile technology-based interventions for adult users of alcohol: a systematic review of the literature. Addict Behav 2016 Nov;62:25-34. [CrossRef] [Medline]
- Jessup MA, Humphreys JC, Brindis CD, Lee KA. Extrinsic barriers to substance abuse treatment among pregnant drug dependent women. J Drug Issue 2016 Aug 03;33(2):285-304. [CrossRef]
- Roberts SC, Pies C. Complex calculations: how drug use during pregnancy becomes a barrier to prenatal care. Matern Child Health J 2010 Mar 16;15(3):333-341. [CrossRef]
- Taylor OD. Barriers to treatment for women with substance use disorders. J Hum Behav Soc Environ 2010 May 10;20(3):393-409. [CrossRef]
- Dauber S, West A, Hammond C, Cohen I, Thrul J. Postpartum heavy episodic drinking: a survey to inform development of a text messaging intervention. Drug Alcohol Rev 2022 Jan;41(1):182-187. [CrossRef] [Medline]
- Suffoletto B, Chung T, Muench F, Monti P, Clark DB. A text message intervention with adaptive goal support to reduce alcohol consumption among non-treatment-seeking young adults: non-randomized clinical trial with voluntary length of enrollment. JMIR Mhealth Uhealth 2018 Feb 16;6(2):e35 [FREE Full text] [CrossRef] [Medline]
- Muench F, van Stolk-Cooke K, Kuerbis A, Stadler G, Baumel A, Shao S, et al. A randomized controlled pilot trial of different mobile messaging interventions for problem drinking compared to weekly drink tracking. PLoS One 2017;12(2):e0167900 [FREE Full text] [CrossRef] [Medline]
- O'Reilly H, Hagerty A, O'Donnell S, Farrell A, Hartnett D, Murphy E, et al. Alcohol use disorder and comorbid depression: a randomized controlled trial investigating the effectiveness of supportive text messages in aiding recovery. Alcohol Alcoholism 2019 Jan 09;54(5):551-558. [CrossRef] [Medline]
- Suffoletto B, Kirisci L, Clark DB, Chung T. Which behavior change techniques help young adults reduce binge drinking? A pilot randomized clinical trial of 5 text message interventions. Addict Behav 2019 May;92:161-167. [CrossRef] [Medline]
- Thomas K, Müssener U, Linderoth C, Karlsson N, Bendtsen P, Bendtsen M. Effectiveness of a text messaging-based intervention targeting alcohol consumption among university students: randomized controlled trial. JMIR Mhealth Uhealth 2018 Jun 25;6(6):e146 [FREE Full text] [CrossRef] [Medline]
- Song T, Qian S, Yu P. Mobile health interventions for self-control of unhealthy alcohol use: systematic review. JMIR Mhealth Uhealth 2019 Jan 29;7(1):e10899 [FREE Full text] [CrossRef] [Medline]
- Kazemi DM, Borsari B, Levine MJ, Li S, Lamberson KA, Matta LA. A systematic review of the mHealth interventions to prevent alcohol and substance abuse. J Health Commun 2017 May;22(5):413-432. [CrossRef] [Medline]
- Hall AK, Cole-Lewis H, Bernhardt JM. Mobile text messaging for health: a systematic review of reviews. Annu Rev Public Health 2015 Mar 18;36:393-415 [FREE Full text] [CrossRef] [Medline]
- Nahum-Shani I, Hekler EB, Spruijt-Metz D. Building health behavior models to guide the development of just-in-time adaptive interventions: a pragmatic framework. Health Psychol 2015 Dec;34 Suppl:1209-1219. [CrossRef] [Medline]
- Biaggi A, Conroy S, Pawlby S, Pariante CM. Identifying the women at risk of antenatal anxiety and depression: a systematic review. J Affect Disord 2016 Feb;191:62-77 [FREE Full text] [CrossRef] [Medline]
- Cludius B, Stevens S, Bantin T, Gerlach AL, Hermann C. The motive to drink due to social anxiety and its relation to hazardous alcohol use. Psychol Addict Behav 2013 Sep;27(3):806-813. [CrossRef] [Medline]
- Grant VV, Stewart SH, Mohr CD. Coping-anxiety and coping-depression motives predict different daily mood-drinking relationships. Psychol Addict Behav 2009 Jun;23(2):226-237. [CrossRef] [Medline]
- Kenney S, Abar CC, O'Brien K, Clark G, LaBrie JW. Trajectories of alcohol use and consequences in college women with and without depressed mood. Addict Behav 2016 Feb;53:19-22. [CrossRef]
- Keefe MR, Kajrlsen KA, Lobo ML, Kotzer AM, Dudley WN. Reducing parenting stress in families with irritable infants. Nurs Res 2006;55(3):198-205. [CrossRef] [Medline]
- Dennis C, Ross L. Relationships among infant sleep patterns, maternal fatigue, and development of depressive symptomatology. Birth 2005 Sep;32(3):187-193. [CrossRef] [Medline]
- Law KH, Jackson B, Guelfi K, Nguyen T, Dimmock JA. Understanding and alleviating maternal postpartum distress: perspectives from first-time mothers in Australia. Soc Sci Med 2018 May;204:59-66. [CrossRef] [Medline]
- Olander EK, Darwin ZJ, Atkinson L, Smith DM, Gardner B. Beyond the 'teachable moment' - A conceptual analysis of women's perinatal behaviour change. Women Birth 2016 Jun;29(3):67-71. [CrossRef] [Medline]
- Collins L. In: Fienberg S, editor. Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). Cham, Switzerland: Springer; 2018.
- Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med 2007 May;32(5 Suppl):112-118 [FREE Full text] [CrossRef] [Medline]
- Guastaferro K, Collins LM. Achieving the goals of translational science in public health intervention research: The Multiphase Optimization Strategy (MOST). Am J Public Health 2019 Feb;109(S2):128-129. [CrossRef] [Medline]
- Cox WM, Klinger E. A motivational model of alcohol use. J Abnorm Psychol 1988 May;97(2):168-180. [CrossRef] [Medline]
- Riley WT, Martin CA, Rivera DE, Hekler EB, Adams MA, Buman MP, et al. Development of a dynamic computational model of social cognitive theory. Transl Behav Med 2016 Dec;6(4):483-495 [FREE Full text] [CrossRef] [Medline]
- Hall PA, Fong GT. Temporal self-regulation theory: a model for individual health behavior. Health Psychol Rev 2007 Mar;1(1):6-52. [CrossRef]
- Suffoletto B, Huber J, Kirisci L, Clark D, Chung T. The effect of SMS behavior change techniques on event-level desire to get drunk in young adults. Psychol Addict Behav 2020 Mar;34(2):320-326 [FREE Full text] [CrossRef] [Medline]
- Thomas K, Linderoth C, Bendtsen M, Bendtsen P, Müssener U. Text message-based intervention targeting alcohol consumption among university students: findings from a formative development study. JMIR Mhealth Uhealth 2016 Oct 20;4(4):e119 [FREE Full text] [CrossRef] [Medline]
- Gonzales R, Ang A, Murphy DA, Glik DC, Anglin MD. Substance use recovery outcomes among a cohort of youth participating in a mobile-based texting aftercare pilot program. J Subst Abuse Treat 2014 Jul;47(1):20-26 [FREE Full text] [CrossRef] [Medline]
- Naughton F, Cooper S, Foster K, Emery J, Leonardi-Bee J, Sutton S, et al. Large multi-centre pilot randomized controlled trial testing a low-cost, tailored, self-help smoking cessation text message intervention for pregnant smokers (MiQuit). Addiction 2017 Jul;112(7):1238-1249 [FREE Full text] [CrossRef] [Medline]
- Kuerbis A, Armeli S, Muench F, Morgenstern J. Motivation and self-efficacy in the context of moderated drinking: global self-report and ecological momentary assessment. Psychol Addict Behav 2013 Dec;27(4):934-943 [FREE Full text] [CrossRef] [Medline]
- Michie S, Whittington C, Hamoudi Z, Zarnani F, Tober G, West R. Identification of behaviour change techniques to reduce excessive alcohol consumption. Addiction 2012 Aug;107(8):1431-1440. [CrossRef] [Medline]
- Garnett CV, Crane D, Brown J, Kaner EF, Beyer FR, Muirhead CR, et al. Behavior change techniques used in digital behavior change interventions to reduce excessive alcohol consumption: a meta-regression. Ann Behav Med 2018 May 18;52(6):530-543. [CrossRef] [Medline]
- Fergie L, Campbell KA, Coleman-Haynes T, Ussher M, Cooper S, Coleman T. Identifying effective behavior change techniques for alcohol and illicit substance use during pregnancy: a systematic review. Ann Behav Med 2019 Jul 17;53(8):769-781 [FREE Full text] [CrossRef] [Medline]
- Shiffman S. Ecological momentary assessment (EMA) in studies of substance use. Psychol Assess 2009 Dec;21(4):486-497 [FREE Full text] [CrossRef] [Medline]
- Nguyen N, McQuoid J, Ramo D, Holmes LM, Ling PM, Thrul J. Real-time predictors of smoking among sexual minority and heterosexual young adults: an ecological momentary assessment study. Drug Alcohol Depend 2018 Nov 01;192:51-58 [FREE Full text] [CrossRef] [Medline]
- Maher JP, Dunton GF. Within-day time-varying associations between motivation and movement-related behaviors in older adults. Psychol Sport Exerc 2020 Mar;47:101522. [CrossRef]
- Sanjuan PM, Pearson MR, Fokas K, Leeman LM. A mother's bond: an ecological momentary assessment study of posttraumatic stress disorder symptoms and substance craving during pregnancy. Psychol Addict Behav 2020 Mar;34(2):269-280 [FREE Full text] [CrossRef] [Medline]
- Mendez DD, Sanders SA, Lai Y, Wallace ML, Rathbun SL, Gary-Webb TL, et al. Ecological momentary assessment of stress, racism and other forms of discrimination during pregnancy using smartphone technology. Paediatr Perinat Epidemiol 2020 Sep;34(5):522-531. [CrossRef] [Medline]
- Morgenstern J, Kuerbis A, Houser J, Muench FJ, Shao S, Treloar H. Within-person associations between daily motivation and self-efficacy and drinking among problem drinkers in treatment. Psychol Addict Behav 2016 Sep;30(6):630-638 [FREE Full text] [CrossRef] [Medline]
- Kuerbis A, Lynch KG, Shao S, Morgenstern J. Examining motivational interviewing's effect on confidence and commitment using daily data. Drug Alcohol Depend 2019 Nov 01;204:107472 [FREE Full text] [CrossRef] [Medline]
- Cooper ML, Frone MR, Russell M, Mudar P. Drinking to regulate positive and negative emotions: a motivational model of alcohol use. J Pers Soc Psychol 1995 Nov;69(5):990-1005. [CrossRef] [Medline]
- Votaw VR, Witkiewitz K. Motives for substance use in daily life: a systematic review of studies using ecological momentary assessment. Clin Psychol Sci 2021 Jul 01;9(4):535-562 [FREE Full text] [CrossRef] [Medline]
- Arbeau KJ, Kuiken D, Wild TC. Drinking to enhance and to cope: a daily process study of motive specificity. Addict Behav 2011 Dec;36(12):1174-1183. [CrossRef] [Medline]
- Dvorak RD, Pearson MR, Day AM. Ecological momentary assessment of acute alcohol use disorder symptoms: associations with mood, motives, and use on planned drinking days. Exp Clin Psychopharmacol 2014 Aug;22(4):285-297 [FREE Full text] [CrossRef] [Medline]
- Stevenson BL, Dvorak RD, Kramer MP, Peterson RS, Dunn ME, Leary AV, et al. Within- and between-person associations from mood to alcohol consequences: the mediating role of enhancement and coping drinking motives. J Abnorm Psychol 2019 Nov;128(8):813-822. [CrossRef] [Medline]
- Ehrenberg E, Armeli S, Howland M, Tennen H. A daily process examination of episode-specific drinking to cope motivation among college students. Addict Behav 2016 Jun;57:69-75 [FREE Full text] [CrossRef] [Medline]
- Richardson CM, Hoene TH, Rigatti HL. Self-critical perfectionism and daily drinking to cope with negative emotional experiences among college students. Personal Individ Diff 2020 Apr;156:109773. [CrossRef]
- O'Hara RE, Boynton MH, Scott DM, Armeli S, Tennen H, Williams C, et al. Drinking to cope among African American college students: an assessment of episode-specific motives. Psychol Addict Behav 2014 Sep;28(3):671-681 [FREE Full text] [CrossRef] [Medline]
- Dworkin ER, Cadigan J, Hughes T, Lee C, Kaysen D. Sexual identity of drinking companions, drinking motives, and drinking behaviors among young sexual minority women: an analysis of daily data. Psychol Addict Behav 2018 Dec;32(5):540-551. [CrossRef] [Medline]
- O'Donnell R, Richardson B, Fuller-Tyszkiewicz M, Liknaitzky P, Arulkadacham L, Dvorak R, et al. Ecological momentary assessment of drinking in young adults: an investigation into social context, affect and motives. Addict Behav 2019 Nov;98:106019. [CrossRef] [Medline]
- Goldbeck R, Myatt P, Aitchison T. End-of-treatment self-efficacy: a predictor of abstinence. Addiction 1997 Mar;92(3):313-324. [Medline]
- Ilgen M, McKellar J, Tiet Q. Abstinence self-efficacy and abstinence 1 year after substance use disorder treatment. J Consult Clin Psychol 2005 Dec;73(6):1175-1180. [CrossRef]
- Kadden RM, Litt MD. The role of self-efficacy in the treatment of substance use disorders. Addict Behav 2011 Dec;36(12):1120-1126 [FREE Full text] [CrossRef] [Medline]
- Long CG, Hollin CR, Williams MJ. Self-efficacy, outcome expectations, and fantasies as predictors of alcoholics' postreatment drinking. Subst Use Misuse 1998 Oct;33(12):2383-2402. [CrossRef] [Medline]
- Müller A, Znoj H, Moggi F. How are self-efficacy and motivation related to drinking five years after residential treatment? A longitudinal multicenter study. Eur Addict Res 2019;25(5):213-223 [FREE Full text] [CrossRef] [Medline]
- Brinken L, Schüz B, Ferguson SG, Scholz U, Schüz N. Social cognitions and smoking behaviour: temporal resolution matters. Br J Health Psychol 2020 Feb;25(1):210-227. [CrossRef] [Medline]
- Bolman C, Verboon P, Thewissen V, Boonen V, Soons K, Jacobs N. Predicting smoking lapses in the first week of quitting: an ecological momentary assessment study. J Addict Med 2018;12(1):65-71 [FREE Full text] [CrossRef] [Medline]
- Tate SR, Wu J, McQuaid JR, Cummins K, Shriver C, Krenek M, et al. Comorbidity of substance dependence and depression: role of life stress and self-efficacy in sustaining abstinence. Psychol Addict Behav 2008;22(1):47-57. [CrossRef]
- Ralston TE, Palfai TP. Effects of depressed mood on drinking refusal self-efficacy: examining the specificity of drinking contexts. Cognit Behav Ther 2010 Dec;39(4):262-269. [CrossRef]
- Yap DF, Nasir N, Tan KS, Lau LH. Variables which predict maternal self-efficacy: a hierarchical linear regression analysis. J Appl Res Intellect Disabil 2019 Jul;32(4):841-848. [CrossRef] [Medline]
- Bolten MI, Fink NS, Stadler C. Maternal self-efficacy reduces the impact of prenatal stress on infant's crying behavior. J Pediatr 2012 Jul;161(1):104-109. [CrossRef] [Medline]
- Denis A, Ponsin M, Callahan S. The relationship between maternal self-esteem, maternal competence, infant temperament and post-partum blues. J Reproduct Infant Psychol 2012 Sep 24;30(4):388-397. [CrossRef]
- Kohlhoff J, Barnett B. Parenting self-efficacy: links with maternal depression, infant behaviour and adult attachment. Early Hum Dev 2013 Apr;89(4):249-256. [CrossRef] [Medline]
- Porter CL, Hsu H. First-time mothers' perceptions of efficacy during the transition to motherhood: links to infant temperament. J Fam Psychol 2003 Mar;17(1):54-64. [Medline]
- Jover M, Colomer J, Carot JM, Larsson C, Bobes MT, Ivorra JL, et al. Maternal anxiety following delivery, early infant temperament and mother's confidence in caregiving. Span J Psychol 2014 Dec 22;17:E95. [CrossRef] [Medline]
- Haslam DM, Pakenham KI, Smith A. Social support and postpartum depressive symptomatology: the mediating role of maternal self-efficacy. Infant Ment Health J 2006 May;27(3):276-291. [CrossRef] [Medline]
- Leahy-Warren P, McCarthy G, Corcoran P. First-time mothers: social support, maternal parental self-efficacy and postnatal depression. J Clin Nurs 2012 Feb;21(3-4):388-397. [CrossRef] [Medline]
- Warner LM, Stadler G, Lüscher J, Knoll N, Ochsner S, Hornung R, et al. Day-to-day mastery and self-efficacy changes during a smoking quit attempt: two studies. Br J Health Psychol 2018 May;23(2):371-386. [CrossRef] [Medline]
- Protogerou C, McHugh RK, Johnson BT. How best to reduce unhealthy risk-taking behaviours? A meta-review of evidence syntheses of interventions using self-regulation principles. Health Psychol Rev 2020 Mar;14(1):86-115. [CrossRef] [Medline]
- Baumeister RF, Vonasch AJ. Uses of self-regulation to facilitate and restrain addictive behavior. Addict Behav 2015 May;44:3-8. [CrossRef] [Medline]
- Roos CR, Kober H, Trull TJ, MacLean RR, Mun CJ. Intensive longitudinal methods for studying the role of self-regulation strategies in substance use behavior change. Curr Addict Rep 2020 Sep;7(3):301-316 [FREE Full text] [CrossRef] [Medline]
- Roos CR, Witkiewitz K. A contextual model of self-regulation change mechanisms among individuals with addictive disorders. Clin Psychol Rev 2017 Nov;57:117-128 [FREE Full text] [CrossRef] [Medline]
- Carroll KM, Onken LS. Behavioral therapies for drug abuse. Am J Psychiatry 2005 Aug;162(8):1452-1460 [FREE Full text] [CrossRef] [Medline]
- McHugh RK, Hearon BA, Otto MW. Cognitive behavioral therapy for substance use disorders. Psychiatr Clin North Am 2010 Sep;33(3):511-525 [FREE Full text] [CrossRef] [Medline]
- Aldridge-Gerry AA, Roesch SC, Villodas F, McCabe C, Leung QK, Da Costa M. Daily stress and alcohol consumption: modeling between-person and within-person ethnic variation in coping behavior. J Stud Alcohol Drugs 2011 Jan;72(1):125-134 [FREE Full text] [CrossRef] [Medline]
- Litt MD, Kadden RM, Kabela-Cormier E. Individualized assessment and treatment program for alcohol dependence: results of an initial study to train coping skills. Addiction 2009 Nov;104(11):1837-1838 [FREE Full text] [CrossRef] [Medline]
- Lewis MA, Patrick ME, Lee CM, Kaysen DL, Mittman A, Neighbors C. Use of protective behavioral strategies and their association to 21st birthday alcohol consumption and related negative consequences: a between- and within-person evaluation. Psychol Addict Behav 2012 Jun;26(2):179-186 [FREE Full text] [CrossRef] [Medline]
- Linden-Carmichael AN, Calhoun BH, Patrick ME, Maggs JL. Are protective behavioral strategies associated with fewer negative consequences on high-intensity drinking days? Results from a measurement-burst design. Psychol Addict Behav 2018 Dec;32(8):904-913 [FREE Full text] [CrossRef] [Medline]
- Dulin PL, Gonzalez VM. Smartphone-based, momentary intervention for alcohol cravings amongst individuals with an alcohol use disorder. Psychol Addict Behav 2017 Dec;31(5):601-607 [FREE Full text] [CrossRef] [Medline]
- McQuoid J, Thrul J, Ling P. A geographically explicit ecological momentary assessment (GEMA) mixed method for understanding substance use. Soc Sci Med 2018 Apr;202:89-98. [CrossRef] [Medline]
- Blevins CE, Marsh EL, Stein MD, Schatten HT, Abrantes AM. Project CHOICE: choosing healthy options in coping with emotions, an EMA/EMI plus in-person intervention for alcohol use. Subst Abus 2021;42(4):569-576. [CrossRef] [Medline]
- Stevenson BL, Blevins CE, Marsh E, Feltus S, Stein M, Abrantes AM. An ecological momentary assessment of mood, coping and alcohol use among emerging adults in psychiatric treatment. Am J Drug Alcohol Abuse 2020 Sep 02;46(5):651-658. [CrossRef] [Medline]
- Sanjuan PM, Pearson MR, Poremba C, Amaro HD, Leeman L. An ecological momentary assessment study examining posttraumatic stress disorder symptoms, prenatal bonding, and substance use among pregnant women. Drug Alcohol Depend 2019 Feb;195:33-39. [CrossRef]
- Leach LS, Butterworth P, Poyser C, Batterham PJ, Farrer LM. Online recruitment: feasibility, cost, and representativeness in a study of postpartum women. J Med Internet Res 2017 Mar 08;19(3):e61 [FREE Full text] [CrossRef] [Medline]
- Badr HA, Zauszniewski JA, Quinn Griffin M, Burant CJ, Przeworski A, Almutairi WM, et al. Effects of postpartum fatigue and depressive cognitions on life satisfaction and quality of life in Arab postpartum women: the intervening role of resourcefulness. Nurs Rep 2021 Feb 04;11(1):84-94 [FREE Full text] [CrossRef] [Medline]
- Laws RA, Litterbach EV, Denney-Wilson EA, Russell CG, Taki S, Ong K, et al. A comparison of recruitment methods for an mHealth intervention targeting mothers: lessons from the growing healthy program. J Med Internet Res 2016 Sep 15;18(9):e248 [FREE Full text] [CrossRef] [Medline]
- Thornton LK, Harris K, Baker A, Johnson M, Kay-Lambkin FJ. Recruiting for addiction research via Facebook. Drug Alcohol Rev 2015 Jul 14;35(4):494-502. [CrossRef] [Medline]
- Goodell EM, Nordeck C, Finan PH, Vandrey R, Dunn KE, Thrul J. Feasibility and acceptability of using smartphone-based EMA to assess patterns of prescription opioid and medical cannabis use among individuals with chronic pain. Internet Interv 2021 Dec;26:100460 [FREE Full text] [CrossRef] [Medline]
- Oei TP, Hasking PA, Young RM. Drinking refusal self-efficacy questionnaire-revised (DRSEQ-R): a new factor structure with confirmatory factor analysis. Drug Alcohol Depend 2005 Jun 01;78(3):297-307. [CrossRef] [Medline]
- American Psychiatric Association adapted NIDA modified ASSIST tools. National Institute on Drug Abuse. 2015. URL: https://www.drugabuse.gov/sites/default/files/pdf/nmassist.pdf [accessed 2022-01-15]
- Recommended alcohol questions [Online]. National Institute on Alcohol Abuse and Alcoholism. 2003. URL: http://www.niaaa.nih.gov/research/guidelines-and-resources/recommended-alcohol-questions [accessed 2021-09-01]
- Ondersma SJ, Chase SK, Svikis DS, Schuster CR. Computer-based brief motivational intervention for perinatal drug use. J Subst Abuse Treat 2005 Jun;28(4):305-312 [FREE Full text] [CrossRef] [Medline]
- Beck A, Steer R, Brown G. Beck Depression Inventory--II. San Antonio, TX: APA PsycTests; 1996.
- Crncec R, Barnett B, Matthey S. Development of an instrument to assess perceived self-efficacy in the parents of infants. Res Nurs Health 2008 Oct;31(5):442-453. [CrossRef] [Medline]
- Murphy A, Steele M, Dube SR, Bate J, Bonuck K, Meissner P, et al. Adverse Childhood Experiences (ACEs) questionnaire and Adult Attachment Interview (AAI): implications for parent child relationships. Child Abuse Negl 2014 Feb;38(2):224-233. [CrossRef] [Medline]
- Harkness A. The Pandemic Stress Index. Miami, FL: University of Miami; 2020.
- Condon JT, Corkindale CJ. The assessment of parent-to-infant attachment: development of a self-report questionnaire instrument. J Reproduct Infant Psychol 1998 Feb;16(1):57-76. [CrossRef]
- Giallo R, Wade C, Kienhuis M. Fatigue in mothers of infants and young children: factor structure of the fatigue assessment scale. Fatigue: Biomed Health Behav 2014 Jul 23;2(3):119-131. [CrossRef]
- Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983 Dec;24(4):385-396. [Medline]
- Chesney MA, Neilands TB, Chambers DB, Taylor JM, Folkman S. A validity and reliability study of the coping self-efficacy scale. Br J Health Psychol 2006 Sep;11(Pt 3):421-437 [FREE Full text] [CrossRef] [Medline]
- Cohen S, Mermelstein R, Kamarck T, Hoberman H. Measuring the functional components of social support. In: Sarason I, Sarason B, editors. Social Support: Theory, Research, and Applications. The Hague, Holland: Martinus Nijhoff; 1985.
- Rosen LD, Whaling K, Carrier LM, Cheever NA, Rokkum J. The Media and Technology Usage and Attitudes Scale: an empirical investigation. Comput Human Behav 2013 Nov 1;29(6):2501-2511 [FREE Full text] [Medline]
- Norman CD, Skinner HA. eHEALS: The eHealth Literacy Scale. J Med Internet Res 2006 Nov;8(4):e27 [FREE Full text] [CrossRef] [Medline]
- Adams L, Igbinedion G, DeVinney A, Azasu E, Nestadt P, Thrul J, et al. Assessing the real-time influence of racism-related stress and suicidality among black men: protocol for an ecological momentary assessment study. JMIR Res Protoc 2021 Oct 20;10(10):e31241 [FREE Full text] [CrossRef] [Medline]
- Fridberg DJ, Faria J, Cao D, King AC. Real-time mobile monitoring of drinking episodes in young adult heavy drinkers: development and comparative survey study. JMIR Mhealth Uhealth 2019 Nov 20;7(11):e13765 [FREE Full text] [CrossRef] [Medline]
- Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, et al. Just-in-Time Adaptive Interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support. Ann Behav Med 2016 Sep 23;52(6):446-462. [CrossRef] [Medline]
- Ramanathan N, Swendeman D, Comulada WS, Estrin D, Rotheram-Borus MJ. Identifying preferences for mobile health applications for self-monitoring and self-management: focus group findings from HIV-positive persons and young mothers. Int J Med Inform 2013 Apr;82(4):38-46 [FREE Full text] [CrossRef] [Medline]
- Allen A, Tosun N, Carlson S, Allen S. Postpartum changes in mood and smoking-related symptomatology: an ecological momentary assessment investigation. Nicotine Tob Res 2018 May 03;20(6):681-689. [CrossRef] [Medline]
- Thrul J, Bühler A, Ferguson SG. Situational and mood factors associated with smoking in young adult light and heavy smokers. Drug Alcohol Rev 2014 Jul;33(4):420-427. [CrossRef] [Medline]
- Bates JE, Freeland CA, Lounsbury ML. Measurement of infant difficultness. Child Dev 1979 Sep;50(3):794-803. [Medline]
- Adams EL, Marini ME, Brick TR, Paul IM, Birch LL, Savage JS. Ecological momentary assessment of using food to soothe during infancy in the INSIGHT trial. Int J Behav Nutr Phys Act 2019 Sep 05;16(1):79 [FREE Full text] [CrossRef] [Medline]
- McNamara TK, Orav EJ, Wilkins-Haug L, Chang G. Social support and prenatal alcohol use. J Womens Health (Larchmt) 2006;15(1):70-76 [FREE Full text] [CrossRef] [Medline]
- Cambron C, Haslam AK, Baucom BR, Lam C, Vinci C, Cinciripini P, et al. Momentary precipitants connecting stress and smoking lapse during a quit attempt. Health Psychol 2019 Dec;38(12):1049-1058. [CrossRef]
- Barnes CR, Adamson-Macedo EN. Perceived Maternal Parenting Self-Efficacy (PMP S-E) tool: development and validation with mothers of hospitalized preterm neonates. J Adv Nurs 2007 Dec;60(5):550-560. [CrossRef] [Medline]
- Thrul J, Gubner NR, Nguyen N, Nguyen C, Goodell EA, Holmes LM, et al. Perceived reward from using cigarettes with alcohol or cannabis and concurrent use: a smartphone-based daily diary study. Addict Behav 2021 Mar;114:106747 [FREE Full text] [CrossRef] [Medline]
- Czyz EK, King CA, Nahum-Shani I. Ecological assessment of daily suicidal thoughts and attempts among suicidal teens after psychiatric hospitalization: lessons about feasibility and acceptability. Psychiatry Res 2018 Sep;267:566-574 [FREE Full text] [CrossRef] [Medline]
- Jones KK, Zenk SN, McDonald A, Corte C. Experiences of African-American women with smartphone-based ecological momentary assessment. Public Health Nurs 2015 Nov 4;33(4):371-380. [CrossRef] [Medline]
- Marcano Belisario JS, Doherty K, O'Donoghue J, Ramchandani P, Majeed A, Doherty G, et al. A bespoke mobile application for the longitudinal assessment of depression and mood during pregnancy: protocol of a feasibility study. BMJ Open 2017 May 29;7(5):e014469 [FREE Full text] [CrossRef] [Medline]
- Srinivas P, Bodke K, Ofner S, Keith NR, Tu W, Clark DO. Context-sensitive ecological momentary assessment: application of user-centered design for improving user satisfaction and engagement during self-report. JMIR Mhealth Uhealth 2019 Apr 03;7(4):e10894. [CrossRef]
- Smiley SL, Elmasry H, Hooper MW, Niaura RS, Hamilton AB, Milburn NG. Feasibility of ecological momentary assessment of daily sexting and substance use among young adult African American gay and bisexual men: a pilot study. JMIR Res Protoc 2017 Feb 02;6(2):e9 [FREE Full text] [CrossRef] [Medline]
- Mackesy-Amiti ME, Boodram B. Feasibility of ecological momentary assessment to study mood and risk behavior among young people who inject drugs. Drug Alcohol Depend 2018 Dec 01;187:227-235. [CrossRef] [Medline]
- Demirci JR, Bogen DL. An ecological momentary assessment of primiparous women’s breastfeeding behavior and problems from birth to 8 weeks. J Hum Lact 2017 Mar 23;33(2):285-295. [CrossRef]
- Burke LE, Shiffman S, Music E, Styn MA, Kriska A, Smailagic A, et al. Ecological momentary assessment in behavioral research: addressing technological and human participant challenges. J Med Internet Res 2017 Mar 15;19(3):e77 [FREE Full text] [CrossRef] [Medline]
- Mohr CD, Arpin S, McCabe CT. Daily affect variability and context-specific alcohol consumption. Drug Alcohol Rev 2015 Nov;34(6):581-587. [CrossRef] [Medline]
- Slavish DC, Scaglione NM, Hultgren BA, Turrisi R. An ecological momentary assessment of affect, mental health symptoms, and decisions to drink among first-year college women: a pilot study. Prev Sci 2019 Jul;20(5):753-764 [FREE Full text] [CrossRef] [Medline]
- Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics 1988 Dec;44(4):1049-1060. [Medline]
- Shiffman S. Conceptualizing analyses of ecological momentary assessment data. Nicotine Tob Res 2014 May;16 Suppl 2:76-87 [FREE Full text] [CrossRef] [Medline]
- Kuntsche E, Kuntsche S, Thrul J, Gmel G. Binge drinking: health impact, prevalence, correlates and interventions. Psychol Health 2017 May 17;32(8):976-1017. [CrossRef]
- van Lier HG, Pieterse ME, Schraagen JM, Postel MG, Vollenbroek-Hutten MM, de Haan HA, et al. Identifying viable theoretical frameworks with essential parameters for real-time and real world alcohol craving research: a systematic review of craving models. Addict Res Theory 2017 Apr 13;26(1):35-51. [CrossRef]
- Perski O, Hébert ET, Naughton F, Hekler EB, Brown J, Businelle MS. Technology-mediated just-in-time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review. Addiction 2021 Sep 13:1-22. [CrossRef] [Medline]
- Gomez KU, Goodwin L, Jackson L, Jones A, Chisholm A, Rose AK. Are psychosocial interventions effective in reducing alcohol consumption during pregnancy and motherhood? A systematic review and meta‐analysis. Addiction 2020 Dec 10;116(7):1638-1663. [CrossRef]
- Frazer Z, McConnell K, Jansson LM. Treatment for substance use disorders in pregnant women: motivators and barriers. Drug Alcohol Depend 2019 Dec;205:107652. [CrossRef]
- Paris R, Herriott AL, Maru M, Hacking SE, Sommer AR. Secrecy versus disclosure: women with substance use disorders share experiences in help seeking during pregnancy. Matern Child Health J 2020 Nov;24(11):1396-1403. [CrossRef] [Medline]
- Wolfson L, Schmidt RA, Stinson J, Poole N. Examining barriers to harm reduction and child welfare services for pregnant women and mothers who use substances using a stigma action framework. Health Soc Care Community 2021 Mar 13;29(3):589-601. [CrossRef]
- Adams ZM, Ginapp CM, Price CR, Qin Y, Madden LM, Yonkers K, et al. “A good mother”: impact of motherhood identity on women's substance use and engagement in treatment across the lifespan. J Substan Abuse Treat 2021 Nov;130:108474. [CrossRef]
- Kenny KS, Barrington C. “People just don't look at you the same way”: public stigma, private suffering and unmet social support needs among mothers who use drugs in the aftermath of child removal. Child Youth Serv Rev 2018 Feb;86:209-216. [CrossRef]
- Jarlenski M, Krans EE. Co-occurring substance use disorders identified among delivery hospitalizations in the United States. J Addict Med 2021;15(6):504-507 [FREE Full text] [CrossRef] [Medline]
- Page K, Murray-Krezan C, Leeman L, Carmody M, Stephen JM, Bakhireva LN. Prevalence of marijuana use in pregnant women with concurrent opioid use disorder or alcohol use in pregnancy. Addict Sci Clin Pract 2022 Jan 06;17(1):3 [FREE Full text] [CrossRef] [Medline]
- Jones HE, Hairston E, Lensch AC, Marcus LK, Heil SH. Challenges and opportunities during the COVID-19 pandemic: treating patients for substance use disorders during the perinatal period. Prevent Med 2021 Nov;152:106742. [CrossRef]
- Mayopoulos GA, Ein-Dor T, Dishy GA, Nandru R, Chan SJ, Hanley LE, et al. COVID-19 is associated with traumatic childbirth and subsequent mother-infant bonding problems. J Affect Disord 2021 Mar;282:122-125. [CrossRef]
- Omowale S, Casas A, Lai Y, Sanders S, Hill A, Wallace M. Trends in stress throughout pregnancy and postpartum period during the COVID-19 pandemic: Longitudinal study using ecological momentary assessment and data from the Postpartum Mothers Mobile Study. JMIR Mental Health 2021;8(9):e30422. [CrossRef]
- Nidey N, Kair L, Wilder C, Froehlich T, Weber S, Folger A. Substance use and utilization of prenatal and postpartum care. J Addict Medi 2022:16-92. [CrossRef]
- Renbarger KM, Shieh C, Moorman M, Latham-Mintus K, Draucker C. Health care encounters of pregnant and postpartum women with substance use disorders. West J Nurs Res 2019 Dec 20;42(8):612-618. [CrossRef]
- Lara-Cinisomo S, Olarte AR, Rosales M, Barrera AZ. A systematic review of technology-based prevention and treatment interventions for perinatal depression and anxiety in Latina and African American women. Matern Child Health J 2021 Feb;25(2):268-281. [CrossRef] [Medline]
- Blakey JM, Hatcher SS. Trauma and substance abuse among child welfare involved African American mothers: a case study. J Public Child Welfare 2013 Apr;7(2):194-216. [CrossRef]
- Martin CE, Scialli A, Terplan M. Unmet substance use disorder treatment need among reproductive age women. Drug Alcohol Depend 2020 Jan;206:107679. [CrossRef]
|CI: Central Intake|
|EMA: ecological momentary assessment|
|JITAI: just-in-time adaptive intervention|
|MOST: multiphase optimization strategy|
|TMI: text messaging intervention|
Edited by T Leung; This paper was externally peer reviewed by the Interventions to Prevent and Treat Addictions (IPTA) Study Section - Risk, Prevention and Health Behavior Integrated Review Group - Center for Scientific Review (National Institutes of Health, USA). See the Multimedia Appendix for the peer-review report;submitted 27.01.22; accepted 01.03.22; published 04.04.22Copyright
©Sarah Dauber, Alexa Beacham, Cori Hammond, Allison West, Johannes Thrul. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 04.04.2022.
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